TFM2_18S_amplicons_analysis
lrubinat
3/9/2017
1) 18S amplicons
1.1) Data overview
The dataset “Malaspina 18S iTags” contains reads from 122 samples of Malaspina. On average, each sample contains 126100 OTUs:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 4050 59560 98630 126100 157000 935800
Overall reads per sample:
1.2) Normalization
In order to keep as many samples as possible, we rarefy at 49975 reads per sample. By that, we loose 31 samples, and after removing the exluded samples in the 16S dataset (to make them comparable), we end up with a normalized dataset containing 43 samples and 5669 OTUs.
tb18_tax_occur_min49975_t<-t(tb18_tax_occur_min49975)
tb18_tax_occur_ss49975<-rrarefy(tb18_tax_occur_min49975_t, 49975)The normalized table shows the following dimensions and format:
## [1] 91 43734## OTU_2 OTU_106 OTU_403 OTU_139 OTU_4
## st055_MD1013 8998 718 80 104 225
## st057_MD1042 2642 241 45 29 121
## st058_MD1080 1305 866 3 17 46
## st059_MD1100 423 705 12 33 182
## st009_MD111 2212 8 0 60 94Its content fits with the expected normalization values (49975 reads per station):
rowSums(tb18_tax_occur_ss49975)## st055_MD1013 st057_MD1042 st058_MD1080 st059_MD1100 st009_MD111
## 49975 49975 49975 49975 49975
## st060_MD1125 st062_MD1143 st065_MD1209 st066_MD1222 st068b_MD1260
## 49975 49975 49975 49975 49975
## st069_MD1293 st070_MD1302 st072_MD1331 st073_MD1354 st074_MD1368
## 49975 49975 49975 49975 49975
## st075_MD1398 st010_MD141 st076_MD1421 st077_MD1425 st078_MD1459
## 49975 49975 49975 49975 49975
## st079_MD1475 st081_MD1479 st082_MD1490 st085_MD1537 st086_MD1559
## 49975 49975 49975 49975 49975
## st087_MD1589 st088_MD1607 st089_MD1629 st092_MD1672 st093_MD1700
## 49975 49975 49975 49975 49975
## st094_MD1724 st095_MD1744 st096_MD1772 st097_MD1798 st098_MD1811
## 49975 49975 49975 49975 49975
## st101_MD1857 st102_MD1885 st103_MD1887 st104_MD1928 st106_MD1956
## 49975 49975 49975 49975 49975
## st107_MD1964 st012_MD196 st108_MD2004 st109_MD2008 st110_MD2047
## 49975 49975 49975 49975 49975
## st112_MD2051 st114_MD2094 st115_MD2111 st014_MD214 st118_MD2155
## 49975 49975 49975 49975 49975
## st120_MD2243 st126_MD2380 st127_MD2408 st128_MD2436 st129_MD2448
## 49975 49975 49975 49975 49975
## st131_MD2516 st015_MD254 st132_MD2562 st133_MD2594 st017_MD266
## 49975 49975 49975 49975 49975
## st138_MD2723 st140_MD2761 st018_MD285 st143_MD2864 st001_MD28
## 49975 49975 49975 49975 49975
## st145_MD2956 st019_MD311 st022_MD346 st023_MD366 st024_MD389
## 49975 49975 49975 49975 49975
## st002_MD40 st025_MD417 st026_MD439 st027_MD458 st028_MD486
## 49975 49975 49975 49975 49975
## st003_MD52 st032_MD550 st033_MD575 st034_MD591 st005_MD64
## 49975 49975 49975 49975 49975
## st038_MD664 st039_MD684 st040_MD712 st041_MD734 st043_MD753
## 49975 49975 49975 49975 49975
## st044_MD778 st045_MD806 st047_MD854 st049_MD876 st050_MD897
## 49975 49975 49975 49975 49975
## st052_MD940
## 49975Let’s check out how many OTUs don’t appear in the new table:
length(which(colSums(tb18_tax_occur_ss49975)==0)) #8045## [1] 5323There are 8045 OTUs that don’t show any occurrence in the normalized data. Let’s remove them from the table and take a look at its final dimensions:
tb18_tax_occur_ss49975_no_cero<-tb18_tax_occur_ss49975[,-(which(colSums(tb18_tax_occur_ss49975)==0))]
tb18_tax_occur_ss49975_no_cero<-tb18_tax_occur_ss49975_no_cero[mixedorder(row.names(tb18_tax_occur_ss49975_no_cero)),]
dim(tb18_tax_occur_ss49975_no_cero) #91 38645## [1] 91 38411Datasets summary:
dim(tb18_tax) #46690 129## [1] 46690 129dim(tb18_tax_occur) #46690 122## [1] 46690 122dim(tb18_tax_occur_ss49975_no_cero) #91 38645## [1] 91 384111.3) General community analysis
1.3.1) Richness and evenness (Shannon index)
Most of the samples take Shannon Index values around 6:
1.3.2) Richness: OTU number
Lowest number of OTUs per sample:
## [1] 1268Maximum number of OTUs per sample:
## [1] 5187In most of the samples, we can identify between 600 and 700 OTUs:
1.3.3) Index of evenness
1.3.3.1) Pielou’s index
The Pielou index (constrained between 0 and 1) takes values closer to 1 as the variation of species proportion in a sample increases. Most of the samples get values between 0.90 and 0.95, meaning that the numerical composition of different OTUs in a sample is highly variable - there’s no constant presence of dominant species. ’ 
1.3.4) Abundance Models
Most of the OTUs show very few occurrences, suggesting that we will probably be able to identify a significant ammount of rare otus:
1.3.4.1) Rank-Abundance or Dominance/Diversity Model (“radfit”)
The OTUs abundance distribution fits relativelly close to log-normal model.
1.3.4.2) Preston’s Log-normal Model
According to Preston’s lognormal model fitted into groups of species’ frequencies, we’re missing 1588.816 species: ’ 
## Extrapolated Observed Veiled
## 46340.804 43734.000 2606.804
When computing Prestons’ lognormal model fit without pooling data into groups, we miss 1385.371 species: ’ 
## Extrapolated Observed Veiled
## 46197.162 43734.000 2463.1621.3.5) Rarefaction curves of rarefied and non-rarefied datasets
1.3.6) Beta diversity
1.3.6.1) Dissimilarity matrix using Bray-Curtis index:
The Bray-Curtis dissimilarity, constrained between 0 (minimum distance) and 1 (highest dissimilarity) allows us to quantify the differences between samples according to the composition and the relative abundance of their OTUs. In our dataset, most of the samples pairs take dissimilarity values around 0.8, meaning that their composition is substantially different.
1.3.6.2) Hierarchical clustering
The stations seem to form clusters according to geographic localization, but there are no evident clusters separated from the general groups, apart from the one containing TARA_84, TARA_82 and TARA_85.
(To be done: assign Longhurst provinces information to each station and check if any of the central clusters is meaningful regarding to the samples’ geographical location)
1.3.6.3) Non-metric multidimensional scaling
We can identify a prominent group in the central part of the NMDS plot and a few outliers (TARA 82, 84 and 85) in the central-right edge of the plot. The stress parameter takes a value below 0.2, suggesting that the plot is acceptable.
##
## Call:
## monoMDS(dist = tb18_tax_occur_ss49975_no_cero.bray)
##
## Non-metric Multidimensional Scaling
##
## 91 points, dissimilarity 'bray', call 'vegdist(x = tb18_tax_occur_ss49975_no_cero, method = "bray")'
##
## Dimensions: 2
## Stress: 0.2055046
## Stress type 1, weak ties
## Scores scaled to unit root mean square, rotated to principal components
## Stopped after 120 iterations: Stress nearly unchanged (ratio > sratmax)
1.4) Geographical analysis
## Warning in if (class(lats) == "SpatialPoints") lats <- coordinates(lats):
## the condition has length > 1 and only the first element will be usedWorking datasets:
- Community matrix: tb18_tax_occur_ss49975_no_cero
dim(tb18_tax_occur_ss49975_no_cero)## [1] 91 38411tb18_tax_occur_ss49975_no_cero[1:5, 1:5]## OTU_2 OTU_106 OTU_403 OTU_139 OTU_4
## st001_MD28 154 35 0 4 44
## st002_MD40 249 8 10 6 45
## st003_MD52 733 21 41 15 32
## st005_MD64 847 97 11 0 125
## st009_MD111 2212 8 0 60 94- Community Bray-Curtis: tb18_tax_occur_ss49975_no_cero.bray
dim(tb18_tax_occur_ss49975_no_cero.bray)## [1] 91 91- Stations distances in km: geo_distances_MP_18S
dim(geo_distances_MP_18S)## [1] 91 91Communities quickly change their composition across geographical distances:
plot(geo_distances_MP_18S, tb18_tax_occur_ss49975_no_cero.bray, pch=19, cex=0.4, xlab="Geopgraphical distances", ylab="Bray-Curtis dissimilarities")
1.4.1) Mantel correlograms
Mantel statistic is -significantlly- so low, meaning that the correlation between samples dissimilarity and geographical distances is weak.
mantel(geo_distances_MP_18S, tb18_tax_occur_ss49975_no_cero.bray)##
## Mantel statistic based on Pearson's product-moment correlation
##
## Call:
## mantel(xdis = geo_distances_MP_18S, ydis = tb18_tax_occur_ss49975_no_cero.bray)
##
## Mantel statistic r: 0.1713
## Significance: 0.001
##
## Upper quantiles of permutations (null model):
## 90% 95% 97.5% 99%
## 0.0208 0.0277 0.0326 0.0378
## Permutation: free
## Number of permutations: 999Maximum distance between samples:
## [1] 19500.19Minimum distance between samples:
## [1] 0Correlograms:
MP_18s_ss49975_mantel_correl_by_1000km<-mantel.correlog(tb18_tax_occur_ss49975_no_cero.bray, D.geo=geo_distances_MP_18S, break.pts=seq(0,20000, by=1000))
plot(MP_18s_ss49975_mantel_correl_by_1000km)
MP_18s_ss49975_mantel_correl_by_100km<-mantel.correlog(tb18_tax_occur_ss49975_no_cero.bray, D.geo=geo_distances_MP_18S, break.pts=seq(0,20000, by=100))
plot(MP_18s_ss49975_mantel_correl_by_100km)
1.5) Abundance vs. occurence
In the following plot, we can appreciate the OTUs distribution according to their percentage of occurence and relative abundance. The red line keeps up OTUs that occur in more than 80% of the samples, the green line limits regionally rare OTUs (< 0.001%), and the blue one restricts regionally abundant OTUs (> 0.1%).
Regionally abundant OTUs (relative abundance over 0.1%):
tb18_ss49975_abundant_sorted_prov<-cbind(otu_names=row.names(tb18_ss49975_abundant_sorted),tb18_ss49975_abundant_sorted)## otu_names mean_rabund perc_occur SILVA_plus_MAS_plus_BM_classif
## 1 OTU_1 0.008781754 100.00000 Dinophyceae
## 2 OTU_10 0.004581192 92.30769 <NA>
## 3 OTU_100 0.001011275 68.13187 <NA>
## 4 OTU_101 0.002365139 85.71429 <NA>
## 5 OTU_102 0.001926458 80.21978 <NA>
## 6 OTU_10246 0.001132434 73.62637 <NA>
## 7 OTU_103 0.001537692 90.10989 <NA>
## 8 OTU_104 0.001532195 80.21978 <NA>
## 9 OTU_105 0.001428626 49.45055 <NA>
## 10 OTU_106 0.003967478 87.91209 <NA>
## 11 OTU_108 0.001561220 72.52747 <NA>
## 12 OTU_109 0.001797602 68.13187 <NA>
## 13 OTU_11 0.007027030 100.00000 <NA>
## 14 OTU_110 0.001648736 85.71429 Dinophyceae
## 15 OTU_111 0.001400261 93.40659 Dinophyceae
## 16 OTU_112 0.001392564 94.50549 Dinophyceae
## 17 OTU_113 0.001131995 72.52747 <NA>
## 18 OTU_1136 0.001319561 98.90110 Dinophyceae
## 19 OTU_11454 0.001878742 100.00000 <NA>
## 20 OTU_115 0.001262389 46.15385 <NA>
## 21 OTU_116 0.001794744 83.51648 <NA>
## 22 OTU_117 0.001035463 91.20879 <NA>
## 23 OTU_118 0.001049096 70.32967 <NA>
## 24 OTU_11833 0.001184988 84.61538 <NA>
## 25 OTU_119 0.002803160 29.67033 <NA>
## 26 OTU_12 0.008681264 100.00000 <NA>
## 27 OTU_120 0.001065148 69.23077 <NA>
## 28 OTU_121 0.001660611 98.90110 Dinophyceae
## 29 OTU_122 0.001206757 64.83516 <NA>
## 30 OTU_123 0.001049316 75.82418 <NA>
## 31 OTU_124 0.001658851 85.71429 <NA>
## 32 OTU_125 0.001231165 96.70330 <NA>
## 33 OTU_126 0.001683039 96.70330 <NA>
## 34 OTU_128 0.001140131 85.71429 <NA>
## 35 OTU_129 0.001122100 68.13187 Chrysophyceae
## 36 OTU_13 0.007213057 98.90110 <NA>
## 37 OTU_130 0.001101650 98.90110 <NA>
## 38 OTU_131 0.001242819 96.70330 Dictyochophyceae
## 39 OTU_132 0.001200600 58.24176 <NA>
## 40 OTU_133 0.001020510 58.24176 <NA>
## 41 OTU_135 0.001377832 89.01099 Chrysophyceae
## 42 OTU_136 0.001136832 52.74725 <NA>
## 43 OTU_137 0.002192965 60.43956 <NA>
## 44 OTU_14 0.003648857 92.30769 <NA>
## 45 OTU_140 0.001131115 80.21978 <NA>
## 46 OTU_141 0.001076802 68.13187 <NA>
## 47 OTU_142 0.001212474 73.62637 Prasinophyceae_clade-IX
## 48 OTU_144 0.001016552 91.20879 <NA>
## 49 OTU_145 0.001233364 90.10989 <NA>
## 50 OTU_146 0.001207197 68.13187 <NA>
## 51 OTU_14696 0.006999324 96.70330 <NA>
## 52 OTU_15 0.003874904 52.74725 <NA>
## 53 OTU_151 0.001051295 69.23077 Chrysophyceae
## 54 OTU_157 0.001029966 45.05495 <NA>
## 55 OTU_16 0.002029146 37.36264 Prasinophyceae_clade-VII
## 56 OTU_161 0.001166078 57.14286 <NA>
## 57 OTU_162 0.001254254 78.02198 <NA>
## 58 OTU_163 0.001052174 76.92308 <NA>
## 59 OTU_165 0.001165198 79.12088 <NA>
## 60 OTU_17 0.004120962 94.50549 <NA>
## 61 OTU_174 0.001125618 73.62637 <NA>
## 62 OTU_177 0.001247437 93.40659 <NA>
## 63 OTU_179 0.001122759 76.92308 <NA>
## 64 OTU_18 0.006851118 100.00000 Dinophyceae
## 65 OTU_180 0.001235783 70.32967 <NA>
## 66 OTU_1819 0.001154203 68.13187 <NA>
## 67 OTU_1842 0.001043819 95.60440 Dinophyceae
## 68 OTU_188 0.001347927 96.70330 Dinophyceae
## 69 OTU_1882 0.001431925 68.13187 <NA>
## 70 OTU_19 0.004458713 100.00000 <NA>
## 71 OTU_192 0.001203019 96.70330 <NA>
## 72 OTU_2 0.035255650 100.00000 <NA>
## 73 OTU_20 0.007444821 56.04396 Pelagophyceae
## 74 OTU_21 0.005340692 94.50549 <NA>
## 75 OTU_22 0.004716644 90.10989 <NA>
## 76 OTU_220 0.001011495 96.70330 <NA>
## 77 OTU_23 0.012380256 96.70330 <NA>
## 78 OTU_235 0.001181250 87.91209 <NA>
## 79 OTU_24 0.006635186 98.90110 <NA>
## 80 OTU_243 0.001311205 97.80220 <NA>
## 81 OTU_25 0.010682484 100.00000 Dinophyceae
## 82 OTU_26 0.005086719 96.70330 <NA>
## 83 OTU_27 0.010048541 100.00000 <NA>
## 84 OTU_28 0.004053675 94.50549 <NA>
## 85 OTU_29 0.002486298 98.90110 <NA>
## 86 OTU_3 0.005880523 85.71429 <NA>
## 87 OTU_30 0.003450297 75.82418 <NA>
## 88 OTU_31 0.003347388 95.60440 <NA>
## 89 OTU_32 0.002116003 79.12088 <NA>
## 90 OTU_33 0.003162021 98.90110 Dinophyceae
## 91 OTU_338 0.001067127 95.60440 Dinophyceae
## 92 OTU_34 0.005884041 71.42857 Chrysophyceae
## 93 OTU_35 0.002532475 87.91209 <NA>
## 94 OTU_35494 0.001214893 67.03297 <NA>
## 95 OTU_35799 0.002920141 100.00000 Dinophyceae
## 96 OTU_36 0.003698772 89.01099 <NA>
## 97 OTU_37 0.002797663 95.60440 <NA>
## 98 OTU_38 0.003267128 92.30769 <NA>
## 99 OTU_39 0.003175434 98.90110 Dinophyceae
## 100 OTU_3988 0.001439181 78.02198 <NA>
## 101 OTU_4 0.007494736 100.00000 Dinophyceae
## 102 OTU_40 0.004197483 100.00000 Dinophyceae
## 103 OTU_41 0.002807778 93.40659 <NA>
## 104 OTU_42 0.002780731 95.60440 <NA>
## 105 OTU_43 0.002653635 69.23077 <NA>
## 106 OTU_44 0.004382191 46.15385 Prasinophyceae
## 107 OTU_45 0.004615934 100.00000 Dinophyceae
## 108 OTU_46 0.002691676 29.67033 Prasinophyceae
## 109 OTU_47 0.003144869 75.82418 <NA>
## 110 OTU_48 0.002605918 93.40659 <NA>
## 111 OTU_49 0.002907608 98.90110 Dinophyceae
## 112 OTU_5 0.004870567 80.21978 <NA>
## 113 OTU_50 0.003971876 96.70330 <NA>
## 114 OTU_51 0.003265369 89.01099 <NA>
## 115 OTU_52 0.002850436 84.61538 <NA>
## 116 OTU_53 0.002072245 39.56044 <NA>
## 117 OTU_54 0.001937672 94.50549 <NA>
## 118 OTU_55 0.003479102 100.00000 <NA>
## 119 OTU_56 0.002308407 61.53846 <NA>
## 120 OTU_5618 0.003488338 94.50549 <NA>
## 121 OTU_57 0.001643679 93.40659 <NA>
## 122 OTU_58 0.002871985 70.32967 <NA>
## 123 OTU_59 0.001691175 79.12088 <NA>
## 124 OTU_6 0.037113722 100.00000 <NA>
## 125 OTU_61 0.001699751 82.41758 <NA>
## 126 OTU_62 0.002200881 82.41758 <NA>
## 127 OTU_63 0.001261070 51.64835 Prasinophyceae_clade-VII
## 128 OTU_6315 0.002216713 92.30769 <NA>
## 129 OTU_64 0.003793985 100.00000 <NA>
## 130 OTU_65 0.002952905 98.90110 <NA>
## 131 OTU_66 0.002519502 97.80220 Dinophyceae
## 132 OTU_67 0.001730975 96.70330 Dinophyceae
## 133 OTU_68 0.002455953 96.70330 <NA>
## 134 OTU_69 0.002547867 57.14286 <NA>
## 135 OTU_7 0.008052598 100.00000 <NA>
## 136 OTU_70 0.003676564 76.92308 <NA>
## 137 OTU_71 0.002642200 100.00000 <NA>
## 138 OTU_72 0.003091436 98.90110 <NA>
## 139 OTU_73 0.002135573 72.52747 <NA>
## 140 OTU_74 0.002443859 95.60440 <NA>
## 141 OTU_75 0.002588767 97.80220 <NA>
## 142 OTU_76 0.001810136 90.10989 <NA>
## 143 OTU_767 0.001113084 28.57143 <NA>
## 144 OTU_77 0.001463149 68.13187 Dinophyceae
## 145 OTU_78 0.002187907 100.00000 Dinophyceae
## 146 OTU_7889 0.002273225 86.81319 <NA>
## 147 OTU_8 0.011284543 98.90110 <NA>
## 148 OTU_80 0.002294774 70.32967 <NA>
## 149 OTU_81 0.003532316 98.90110 <NA>
## 150 OTU_82 0.002167237 89.01099 <NA>
## 151 OTU_83 0.001595083 72.52747 <NA>
## 152 OTU_84 0.003011616 74.72527 <NA>
## 153 OTU_85 0.002143050 92.30769 <NA>
## 154 OTU_87 0.001965598 92.30769 Dictyochophyceae
## 155 OTU_88 0.001378491 92.30769 <NA>
## 156 OTU_89 0.002038382 71.42857 <NA>
## 157 OTU_8924 0.001059651 71.42857 <NA>
## 158 OTU_9 0.007790928 73.62637 <NA>
## 159 OTU_90 0.001698432 96.70330 <NA>
## 160 OTU_91 0.001143649 63.73626 <NA>
## 161 OTU_92 0.002018372 75.82418 <NA>
## 162 OTU_93 0.001216872 91.20879 <NA>
## 163 OTU_94 0.001314943 94.50549 <NA>
## 164 OTU_95 0.001584529 84.61538 <NA>
## 165 OTU_96 0.002072905 65.93407 <NA>
## 166 OTU_98 0.001593984 85.71429 <NA>
## 167 OTU_99 0.001284818 69.23077 <NA>## [1] 167 4Proportion of regionally abundant OTUs (%):
## [1] 0.4347713Cosmopolitan OTUs (relative abundance over 0.1% and occurence in more than 80% of samples):
otu_tb18_ss49975_cosmop_sorted_prov<-merge(otu_tb18_ss49975_cosmop_sorted_prov,tb18_class_prov, by="otu_names", all.x=TRUE)## otu_names mean_rabund perc_occur SILVA_plus_MAS_plus_BM_classif
## 1 OTU_1 0.008781754 100.00000 Dinophyceae
## 2 OTU_10 0.004581192 92.30769 <NA>
## 3 OTU_101 0.002365139 85.71429 <NA>
## 4 OTU_102 0.001926458 80.21978 <NA>
## 5 OTU_103 0.001537692 90.10989 <NA>
## 6 OTU_104 0.001532195 80.21978 <NA>
## 7 OTU_106 0.003967478 87.91209 <NA>
## 8 OTU_11 0.007027030 100.00000 <NA>
## 9 OTU_110 0.001648736 85.71429 Dinophyceae
## 10 OTU_111 0.001400261 93.40659 Dinophyceae
## 11 OTU_112 0.001392564 94.50549 Dinophyceae
## 12 OTU_1136 0.001319561 98.90110 Dinophyceae
## 13 OTU_11454 0.001878742 100.00000 <NA>
## 14 OTU_116 0.001794744 83.51648 <NA>
## 15 OTU_117 0.001035463 91.20879 <NA>
## 16 OTU_11833 0.001184988 84.61538 <NA>
## 17 OTU_12 0.008681264 100.00000 <NA>
## 18 OTU_121 0.001660611 98.90110 Dinophyceae
## 19 OTU_124 0.001658851 85.71429 <NA>
## 20 OTU_125 0.001231165 96.70330 <NA>
## 21 OTU_126 0.001683039 96.70330 <NA>
## 22 OTU_128 0.001140131 85.71429 <NA>
## 23 OTU_13 0.007213057 98.90110 <NA>
## 24 OTU_130 0.001101650 98.90110 <NA>
## 25 OTU_131 0.001242819 96.70330 Dictyochophyceae
## 26 OTU_135 0.001377832 89.01099 Chrysophyceae
## 27 OTU_14 0.003648857 92.30769 <NA>
## 28 OTU_140 0.001131115 80.21978 <NA>
## 29 OTU_144 0.001016552 91.20879 <NA>
## 30 OTU_145 0.001233364 90.10989 <NA>
## 31 OTU_14696 0.006999324 96.70330 <NA>
## 32 OTU_17 0.004120962 94.50549 <NA>
## 33 OTU_177 0.001247437 93.40659 <NA>
## 34 OTU_18 0.006851118 100.00000 Dinophyceae
## 35 OTU_1842 0.001043819 95.60440 Dinophyceae
## 36 OTU_188 0.001347927 96.70330 Dinophyceae
## 37 OTU_19 0.004458713 100.00000 <NA>
## 38 OTU_192 0.001203019 96.70330 <NA>
## 39 OTU_2 0.035255650 100.00000 <NA>
## 40 OTU_21 0.005340692 94.50549 <NA>
## 41 OTU_22 0.004716644 90.10989 <NA>
## 42 OTU_220 0.001011495 96.70330 <NA>
## 43 OTU_23 0.012380256 96.70330 <NA>
## 44 OTU_235 0.001181250 87.91209 <NA>
## 45 OTU_24 0.006635186 98.90110 <NA>
## 46 OTU_243 0.001311205 97.80220 <NA>
## 47 OTU_25 0.010682484 100.00000 Dinophyceae
## 48 OTU_26 0.005086719 96.70330 <NA>
## 49 OTU_27 0.010048541 100.00000 <NA>
## 50 OTU_28 0.004053675 94.50549 <NA>
## 51 OTU_29 0.002486298 98.90110 <NA>
## 52 OTU_3 0.005880523 85.71429 <NA>
## 53 OTU_31 0.003347388 95.60440 <NA>
## 54 OTU_33 0.003162021 98.90110 Dinophyceae
## 55 OTU_338 0.001067127 95.60440 Dinophyceae
## 56 OTU_35 0.002532475 87.91209 <NA>
## 57 OTU_35799 0.002920141 100.00000 Dinophyceae
## 58 OTU_36 0.003698772 89.01099 <NA>
## 59 OTU_37 0.002797663 95.60440 <NA>
## 60 OTU_38 0.003267128 92.30769 <NA>
## 61 OTU_39 0.003175434 98.90110 Dinophyceae
## 62 OTU_4 0.007494736 100.00000 Dinophyceae
## 63 OTU_40 0.004197483 100.00000 Dinophyceae
## 64 OTU_41 0.002807778 93.40659 <NA>
## 65 OTU_42 0.002780731 95.60440 <NA>
## 66 OTU_45 0.004615934 100.00000 Dinophyceae
## 67 OTU_48 0.002605918 93.40659 <NA>
## 68 OTU_49 0.002907608 98.90110 Dinophyceae
## 69 OTU_5 0.004870567 80.21978 <NA>
## 70 OTU_50 0.003971876 96.70330 <NA>
## 71 OTU_51 0.003265369 89.01099 <NA>
## 72 OTU_52 0.002850436 84.61538 <NA>
## 73 OTU_54 0.001937672 94.50549 <NA>
## 74 OTU_55 0.003479102 100.00000 <NA>
## 75 OTU_5618 0.003488338 94.50549 <NA>
## 76 OTU_57 0.001643679 93.40659 <NA>
## 77 OTU_6 0.037113722 100.00000 <NA>
## 78 OTU_61 0.001699751 82.41758 <NA>
## 79 OTU_62 0.002200881 82.41758 <NA>
## 80 OTU_6315 0.002216713 92.30769 <NA>
## 81 OTU_64 0.003793985 100.00000 <NA>
## 82 OTU_65 0.002952905 98.90110 <NA>
## 83 OTU_66 0.002519502 97.80220 Dinophyceae
## 84 OTU_67 0.001730975 96.70330 Dinophyceae
## 85 OTU_68 0.002455953 96.70330 <NA>
## 86 OTU_7 0.008052598 100.00000 <NA>
## 87 OTU_71 0.002642200 100.00000 <NA>
## 88 OTU_72 0.003091436 98.90110 <NA>
## 89 OTU_74 0.002443859 95.60440 <NA>
## 90 OTU_75 0.002588767 97.80220 <NA>
## 91 OTU_76 0.001810136 90.10989 <NA>
## 92 OTU_78 0.002187907 100.00000 Dinophyceae
## 93 OTU_7889 0.002273225 86.81319 <NA>
## 94 OTU_8 0.011284543 98.90110 <NA>
## 95 OTU_81 0.003532316 98.90110 <NA>
## 96 OTU_82 0.002167237 89.01099 <NA>
## 97 OTU_85 0.002143050 92.30769 <NA>
## 98 OTU_87 0.001965598 92.30769 Dictyochophyceae
## 99 OTU_88 0.001378491 92.30769 <NA>
## 100 OTU_90 0.001698432 96.70330 <NA>
## 101 OTU_93 0.001216872 91.20879 <NA>
## 102 OTU_94 0.001314943 94.50549 <NA>
## 103 OTU_95 0.001584529 84.61538 <NA>
## 104 OTU_98 0.001593984 85.71429 <NA>## [1] 104 4Number and proportion (%) of cosmopolitan OTUs:
## [1] 104## [1] 0.2707558Number and proportion (%) of rare OTUs:
nrow(otu_tb18_ss49975_rabund_percoccur[otu_tb18_ss49975_rabund_percoccur$mean_rabund < 0.00001 & otu_tb18_ss49975_rabund_percoccur$mean_rabund >0,])## [1] 32696## [1] 85.121451.6) Taxonomic composition analysis
1.6.1) Normalized data
PHOTOTROPHS + HETEROTROPHS
No. of OTUs and reads of the rearefied dataset:
## [1] 38411## [1] 4547725
Number and proportion (%) of OTUs of phototrophic groups:
## [1] 11850## [1] 30.85054Number and proportion (%) of reads of phototrophic groups:
## [1] 950856## [1] 20.90839
Number and proportion (%) of OTUs of non-phototrophic groups:
## [1] 26561## [1] 69.14946Number and proportion (%) of reads of non-phototrophic groups:
## [1] 3596869## [1] 79.09161
Absolute values
## reads_per_class OTUs_per_class samples_per_class
## 59 1 NA
## Bacillariophyceae 3636 98 88
## Bolidophyceae 2971 15 89
## Chlorarachniophyceae 3335 70 89
## Chrysophyceae 79873 361 91
## Cryptophyceae 9910 77 80
## Dictyochophyceae 39444 237 91
## Dinophyceae 650673 9894 91
## Eustigmatales 232 9 NA
## Heterotrophs 3596869 26561 91
## MOCH-1 4357 70 NA
## MOCH-2 17109 131 NA
## MOCH-5 2431 19 NA
## Mamiellophyceae 340 32 41
## Pelagophyceae 46796 339 90
## Pinguiophyceae 1544 19 86
## Prasinophyceae 51033 191 NA
## Prasinophyceae_clade-IX 11979 79 87
## Prasinophyceae_clade-VII 23960 125 87
## Prymnesiophyceae 399 62 76
## Pyramimonadaceae 113 3 7
## Raphydophyceae 211 4 51
## Trebouxiophyceae 103 3 4
## Ulvophyceae 16 3 4
## other_Prasinophyceae 332 8 54
Relative values
## reads_per_class OTUs_per_class samples_per_class
## 100 100 NA## reads_per_class OTUs_per_class samples_per_class
## 1.297352e-03 0.002603421 NA
## Bacillariophyceae 7.995206e-02 0.255135248 96.703297
## Bolidophyceae 6.532937e-02 0.039051313 97.802198
## Chlorarachniophyceae 7.333337e-02 0.182239463 97.802198
## Chrysophyceae 1.756329e+00 0.939834943 100.000000
## Cryptophyceae 2.179112e-01 0.200463409 87.912088
## Dictyochophyceae 8.673348e-01 0.617010752 100.000000
## Dinophyceae 1.430766e+01 25.758246336 100.000000
## Eustigmatales 5.101452e-03 0.023430788 NA
## Heterotrophs 7.909161e+01 69.149462394 100.000000
## MOCH-1 9.580614e-02 0.182239463 NA
## MOCH-2 3.762101e-01 0.341048137 NA
## MOCH-5 5.345530e-02 0.049464997 NA
## Mamiellophyceae 7.476266e-03 0.083309469 45.054945
## Pelagophyceae 1.028998e+00 0.882559683 98.901099
## Pinguiophyceae 3.395104e-02 0.049464997 94.505495
## Prasinophyceae 1.122165e+00 0.497253391 NA
## Prasinophyceae_clade-IX 2.634064e-01 0.205670251 95.604396
## Prasinophyceae_clade-VII 5.268568e-01 0.325427612 95.604396
## Prymnesiophyceae 8.773618e-03 0.161412095 83.516484
## Pyramimonadaceae 2.484759e-03 0.007810263 7.692308
## Raphydophyceae 4.639682e-03 0.010413684 56.043956
## Trebouxiophyceae 2.264869e-03 0.007810263 4.395604
## Ulvophyceae 3.518243e-04 0.007810263 4.395604
## other_Prasinophyceae 7.300353e-03 0.020827367 59.340659
Reads per class vs. OTUs per class:
Reads per class vs. samples in which they occurr:
PHOTOTROPHS
Absolute values
## reads_per_class OTUs_per_class samples_per_class
## 59 1 NA
## Bacillariophyceae 3636 98 88
## Bolidophyceae 2971 15 89
## Chlorarachniophyceae 3335 70 89
## Chrysophyceae 79873 361 91
## Cryptophyceae 9910 77 80
## Dictyochophyceae 39444 237 91
## Dinophyceae 650673 9894 91
## Eustigmatales 232 9 NA
## MOCH-1 4357 70 NA
## MOCH-2 17109 131 NA
## MOCH-5 2431 19 NA
## Mamiellophyceae 340 32 41
## Pelagophyceae 46796 339 90
## Pinguiophyceae 1544 19 86
## Prasinophyceae 51033 191 NA
## Prasinophyceae_clade-IX 11979 79 87
## Prasinophyceae_clade-VII 23960 125 87
## Prymnesiophyceae 399 62 76
## Pyramimonadaceae 113 3 7
## Raphydophyceae 211 4 51
## Trebouxiophyceae 103 3 4
## Ulvophyceae 16 3 4
## other_Prasinophyceae 332 8 54
Relative values
## reads_per_class OTUs_per_class samples_per_class
## 100 100 NA## reads_per_class OTUs_per_class samples_per_class
## 0.006204935 0.008438819 NA
## Bacillariophyceae 0.382392287 0.827004219 96.703297
## Bolidophyceae 0.312455303 0.126582278 97.802198
## Chlorarachniophyceae 0.350736599 0.590717300 97.802198
## Chrysophyceae 8.400115265 3.046413502 100.000000
## Cryptophyceae 1.042218801 0.649789030 87.912088
## Dictyochophyceae 4.148262197 2.000000000 100.000000
## Dinophyceae 68.430235493 83.493670886 100.000000
## Eustigmatales 0.024399068 0.075949367 NA
## MOCH-1 0.458218700 0.590717300 NA
## MOCH-2 1.799326081 1.105485232 NA
## MOCH-5 0.255664370 0.160337553 NA
## Mamiellophyceae 0.035757255 0.270042194 45.054945
## Pelagophyceae 4.921460242 2.860759494 98.901099
## Pinguiophyceae 0.162380003 0.160337553 94.505495
## Prasinophyceae 5.367058734 1.611814346 NA
## Prasinophyceae_clade-IX 1.259812211 0.666666667 95.604396
## Prasinophyceae_clade-VII 2.519834759 1.054852321 95.604396
## Prymnesiophyceae 0.041962190 0.523206751 83.516484
## Pyramimonadaceae 0.011884029 0.025316456 7.692308
## Raphydophyceae 0.022190531 0.033755274 56.043956
## Trebouxiophyceae 0.010832345 0.025316456 4.395604
## Ulvophyceae 0.001682694 0.025316456 4.395604
## other_Prasinophyceae 0.034915907 0.067510549 59.340659
Reads per class vs. OTUs per class:
Reads per class vs. samples in which they occurr:
1.6.2) Non-rarefied data
PHOTOTROPHS + HETEROTROPHS
No. of OTUs and reads of the rearefied dataset:
## [1] 43734## [1] 12250242No. of OTUs and reads of phototrophic groups:
## [1] 13555## [1] 2515108No. of OTUs and reads of non-phototrophic groups:
## [1] 30179## [1] 9735134
Absolute values
## reads_per_class OTUs_per_class samples_per_class
## 150 1 NA
## Bacillariophyceae 9195 109 89
## Bolidophyceae 7156 16 89
## Chlorarachniophyceae 10036 80 89
## Chrysophyceae 192835 418 91
## Cryptophyceae 27260 95 81
## Dictyochophyceae 104205 264 91
## Dinophyceae 1769257 11319 91
## Eustigmatales 573 9 NA
## Heterotrophs 9735134 30179 91
## MOCH-1 13716 83 NA
## MOCH-2 45703 153 NA
## MOCH-5 7015 25 NA
## Mamiellophyceae 931 35 48
## Pelagophyceae 121087 386 90
## Pinguiophyceae 5296 27 89
## Prasinophyceae 111285 218 NA
## Prasinophyceae_clade-IX 29715 86 87
## Prasinophyceae_clade-VII 56610 133 88
## Prymnesiophyceae 1072 74 80
## Pyramimonadaceae 254 3 7
## Raphydophyceae 664 4 62
## Trebouxiophyceae 193 3 4
## Ulvophyceae 50 3 5
## other_Prasinophyceae 850 11 59
Relative values
## reads_per_class OTUs_per_class samples_per_class
## 100 100 NA## reads_per_class OTUs_per_class samples_per_class
## 1.224466e-03 0.002286551 NA
## Bacillariophyceae 7.505974e-02 0.249234006 97.802198
## Bolidophyceae 5.841517e-02 0.036584808 97.802198
## Chlorarachniophyceae 8.192491e-02 0.182924041 97.802198
## Chrysophyceae 1.574132e+00 0.955778113 100.000000
## Cryptophyceae 2.225262e-01 0.217222298 89.010989
## Dictyochophyceae 8.506363e-01 0.603649335 100.000000
## Dinophyceae 1.444263e+01 25.881465222 100.000000
## Eustigmatales 4.677459e-03 0.020578955 NA
## Heterotrophs 7.946891e+01 69.005807838 100.000000
## MOCH-1 1.119651e-01 0.189783692 NA
## MOCH-2 3.730783e-01 0.349842228 NA
## MOCH-5 5.726417e-02 0.057163763 NA
## Mamiellophyceae 7.599850e-03 0.080029268 52.747253
## Pelagophyceae 9.884458e-01 0.882608497 98.901099
## Pinguiophyceae 4.323180e-02 0.061736864 97.802198
## Prasinophyceae 9.084310e-01 0.498468011 NA
## Prasinophyceae_clade-IX 2.425666e-01 0.196643344 95.604396
## Prasinophyceae_clade-VII 4.621133e-01 0.304111218 96.703297
## Prymnesiophyceae 8.750848e-03 0.169204738 87.912088
## Pyramimonadaceae 2.073428e-03 0.006859652 7.692308
## Raphydophyceae 5.420301e-03 0.009146202 68.131868
## Trebouxiophyceae 1.575479e-03 0.006859652 4.395604
## Ulvophyceae 4.081552e-04 0.006859652 5.494505
## other_Prasinophyceae 6.938638e-03 0.025152056 64.835165
Reads per class vs. OTUs per class:
Reads per class vs. samples in which they occurr:
PHOTOTROPHS
Absolute values
## reads_per_class OTUs_per_class samples_per_class
## 150 1 NA
## Bacillariophyceae 9195 109 89
## Bolidophyceae 7156 16 89
## Chlorarachniophyceae 10036 80 89
## Chrysophyceae 192835 418 91
## Cryptophyceae 27260 95 81
## Dictyochophyceae 104205 264 91
## Dinophyceae 1769257 11319 91
## Eustigmatales 573 9 NA
## MOCH-1 13716 83 NA
## MOCH-2 45703 153 NA
## MOCH-5 7015 25 NA
## Mamiellophyceae 931 35 48
## Pelagophyceae 121087 386 90
## Pinguiophyceae 5296 27 89
## Prasinophyceae 111285 218 NA
## Prasinophyceae_clade-IX 29715 86 87
## Prasinophyceae_clade-VII 56610 133 88
## Prymnesiophyceae 1072 74 80
## Pyramimonadaceae 254 3 7
## Raphydophyceae 664 4 62
## Trebouxiophyceae 193 3 4
## Ulvophyceae 50 3 5
## other_Prasinophyceae 850 11 59
Relative values
## reads_per_class OTUs_per_class samples_per_class
## 100 100 NA## reads_per_class OTUs_per_class samples_per_class
## 0.005963959 0.007377352 NA
## Bacillariophyceae 0.365590663 0.804131317 97.802198
## Bolidophyceae 0.284520585 0.118037624 97.802198
## Chlorarachniophyceae 0.399028590 0.590188122 97.802198
## Chrysophyceae 7.667066384 3.083732940 100.000000
## Cryptophyceae 1.083850077 0.700848395 89.010989
## Dictyochophyceae 4.143162043 1.947620804 100.000000
## Dinophyceae 70.345170068 83.504241977 100.000000
## Eustigmatales 0.022782322 0.066396164 NA
## MOCH-1 0.545344375 0.612320177 NA
## MOCH-2 1.817138668 1.128734784 NA
## MOCH-5 0.278914464 0.184433788 NA
## Mamiellophyceae 0.037016303 0.258207304 52.747253
## Pelagophyceae 4.814385704 2.847657691 98.901099
## Pinguiophyceae 0.210567498 0.199188491 97.802198
## Prasinophyceae 4.424660889 1.608262634 NA
## Prasinophyceae_clade-IX 1.181460200 0.634452232 95.604396
## Prasinophyceae_clade-VII 2.250797978 0.981187754 96.703297
## Prymnesiophyceae 0.042622424 0.545924013 87.912088
## Pyramimonadaceae 0.010098970 0.022132055 7.692308
## Raphydophyceae 0.026400457 0.029509406 68.131868
## Trebouxiophyceae 0.007673627 0.022132055 4.395604
## Ulvophyceae 0.001987986 0.022132055 5.494505
## other_Prasinophyceae 0.033795765 0.081150867 64.835165
Reads per class vs. OTUs per class:
Reads per class vs. samples in which they occurr:
OLD VERSION
1.6) Taxonomic composition analysis
1.6.1) Normalized data
1.6.1.1) Absolute values
Let’s add the taxonomic classification by merging “tb18_tax_occur_ss49975_no_cero” with “tb18_tax”:
## [1] 38411 99## Row.names st001_MD28 st002_MD40 st003_MD52 st005_MD64
## 1 OTU_1 158 136 236 155
## 2 OTU_10 4 49 167 75
## 3 OTU_100 72 221 25 49
## 4 OTU_1000 1 0 8 0
## 5 OTU_10000 1 3 5 0## [1] 38411 98## st001_MD28 st002_MD40 st003_MD52 st005_MD64 st009_MD111
## OTU_1 158 136 236 155 222
## OTU_10 4 49 167 75 84
## OTU_100 72 221 25 49 358
## OTU_1000 1 0 8 0 0
## OTU_10000 1 3 5 0 0## [1] 38411 99## st001_MD28 st002_MD40 st003_MD52 st005_MD64 st009_MD111
## OTU_1 158 136 236 155 222
## OTU_2 154 249 733 847 2212
## OTU_3 350 1481 1571 434 289
## OTU_4 44 45 32 125 94
## OTU_5 0 126 273 45 101## [1] 11850 99#create a table per group and count in how many samples they occur.
Dinophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Dinophyceae"),]
Dinophyceae_tb[1:5,1:5]## st001_MD28 st002_MD40 st003_MD52 st005_MD64 st009_MD111
## NA NA NA NA NA NA
## NA.1 NA NA NA NA NA
## NA.2 NA NA NA NA NA
## NA.3 NA NA NA NA NA
## NA.4 NA NA NA NA NADinophyceae_tb_occur <- Dinophyceae_tb[,1:91]
Dinophyceae_tb_occur[1:5,1:5]## st001_MD28 st002_MD40 st003_MD52 st005_MD64 st009_MD111
## NA NA NA NA NA NA
## NA.1 NA NA NA NA NA
## NA.2 NA NA NA NA NA
## NA.3 NA NA NA NA NA
## NA.4 NA NA NA NA NAdim(Dinophyceae_tb_occur)## [1] 0 91length(Dinophyceae_tb_occur[,colSums(Dinophyceae_tb_occur) > 0])## [1] 0#Dinophyceae_tb_samples <- Dinophyceae_tb_occur[,colSums(Dinophyceae_tb_occur) > 0]
#length(Dinophyceae_tb_samples[which(colSums(Dinophyceae_tb_occur) != 0)])
Prasinophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "other_Prasinophyceae"),]
Prasinophyceae_tb_occur <- Prasinophyceae_tb[,1:91]
length(Prasinophyceae_tb_occur[,colSums(Prasinophyceae_tb_occur) > 0])## [1] 0Chrysophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Chrysophyceae"),]
Chrysophyceae_tb_occur <- Chrysophyceae_tb[,1:91]
length(Chrysophyceae_tb_occur[,colSums(Chrysophyceae_tb_occur) > 0])## [1] 0Pelagophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Pelagophyceae"),]
Pelagophyceae_tb_occur <- Pelagophyceae_tb[,1:91]
length(Pelagophyceae_tb_occur[,colSums(Pelagophyceae_tb_occur) > 0])## [1] 0Dictyochophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Dictyochophyceae"),]
Dictyochophyceae_tb_occur <- Dictyochophyceae_tb[,1:91]
length(Dictyochophyceae_tb_occur[,colSums(Dictyochophyceae_tb_occur) > 0])## [1] 0Cryptomonadales_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Cryptophyceae"),]
Cryptomonadales_tb_occur <- Cryptomonadales_tb[,1:91]
length(Cryptomonadales_tb_occur[,colSums(Cryptomonadales_tb_occur) > 0])## [1] 0Bacillariophyta_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Bacillariophyceae"),]
Bacillariophyta_tb_occur <- Bacillariophyta_tb[,1:91]
length(Bacillariophyta_tb_occur[,colSums(Bacillariophyta_tb_occur) > 0])## [1] 0Chlorarachniophyta_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Chlorarachniophyceae"),]
Chlorarachniophyta_tb_occur <- Chlorarachniophyta_tb[,1:91]
length(Chlorarachniophyta_tb_occur[,colSums(Chlorarachniophyta_tb_occur) > 0])## [1] 0Bolidophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Bolidophyceae"),]
Bolidophyceae_tb_occur <- Bolidophyceae_tb[,1:91]
length(Bolidophyceae_tb_occur[,colSums(Bolidophyceae_tb_occur) > 0])## [1] 0Pinguiochysidales_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Pinguiophyceae"),]
Pinguiochysidales_tb_occur <- Pinguiochysidales_tb[,1:91]
length(Pinguiochysidales_tb_occur[,colSums(Pinguiochysidales_tb_occur) > 0])## [1] 0Prymnesiophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Prymnesiophyceae"),]
Prymnesiophyceae_tb_occur <- Prymnesiophyceae_tb[,1:91]
length(Prymnesiophyceae_tb_occur[,colSums(Prymnesiophyceae_tb_occur) > 0])## [1] 0Mamiellophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Mamiellophyceae"),]
Mamiellophyceae_tb_occur <- Mamiellophyceae_tb[,1:91]
length(Mamiellophyceae_tb_occur[,colSums(Mamiellophyceae_tb_occur) > 0])## [1] 0Eustigmatales_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Eustigmatophyceae"),]
Eustigmatales_tb_occur <- Eustigmatales_tb[,1:91]
length(Eustigmatales_tb_occur[,colSums(Eustigmatales_tb_occur) > 0])## [1] 0Chlorophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Chlorophyceae"),]
Chlorophyceae_tb_occur <- Chlorophyceae_tb[,1:91]
length(Chlorophyceae_tb_occur[,colSums(Chlorophyceae_tb_occur) > 0])## [1] 0Ulvophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Ulvophyceae"),]
Ulvophyceae_tb_occur <- Ulvophyceae_tb[,1:91]
length(Ulvophyceae_tb_occur[,colSums(Ulvophyceae_tb_occur) > 0])## [1] 0Raphydophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Raphydophyceae"),]
Raphydophyceae_tb_occur <- Raphydophyceae_tb[,1:91]
length(Raphydophyceae_tb_occur[,colSums(Raphydophyceae_tb_occur) > 0])## [1] 0Trebouxiophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Trebouxiophyceae"),]
Trebouxiophyceae_tb_occur <- Trebouxiophyceae_tb[,1:91]
length(Trebouxiophyceae_tb_occur[,colSums(Trebouxiophyceae_tb_occur) > 0])## [1] 0Phaeophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Phaeophyceae"),]
Phaeophyceae_tb_occur <- Phaeophyceae_tb[,1:91]
length(Phaeophyceae_tb_occur[,colSums(Phaeophyceae_tb_occur) > 0])## [1] 0Phaeothamniophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Phaeothamniophyceae"),]
Phaeothamniophyceae_tb_occur <- Phaeothamniophyceae_tb[,1:91]
length(Phaeothamniophyceae_tb_occur[,colSums(Phaeothamniophyceae_tb_occur) > 0])## [1] 0Xanthophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Xanthophyceae"),]
Xanthophyceae_tb_occur <- Xanthophyceae_tb[,1:91]
length(Xanthophyceae_tb_occur[,colSums(Xanthophyceae_tb_occur) > 0])## [1] 0Chlorodendrophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Chlorodendrophyceae"),]
Chlorodendrophyceae_tb_occur <- Chlorodendrophyceae_tb[,1:91]
length(Chlorodendrophyceae_tb_occur[,colSums(Chlorodendrophyceae_tb_occur) > 0])## [1] 0IncertaeSedis_Archaeplastida_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "IncertaeSedis_Archaeplastida"),]
IncertaeSedis_Archaeplastida_tb_occur <- IncertaeSedis_Archaeplastida_tb[,1:91]
length(IncertaeSedis_Archaeplastida_tb_occur[,colSums(IncertaeSedis_Archaeplastida_tb_occur) > 0])## [1] 0Nephroselmidophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Nephroselmidophyceae"),]
Nephroselmidophyceae_tb_occur <- Nephroselmidophyceae_tb[,1:91]
length(Nephroselmidophyceae_tb_occur[,colSums(Nephroselmidophyceae_tb_occur) > 0])## [1] 0Pavlovophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Pavlovophyceae"),]
Pavlovophyceae_tb_occur <- Pavlovophyceae_tb[,1:91]
length(Pavlovophyceae_tb_occur[,colSums(Pavlovophyceae_tb_occur) > 0])## [1] 0Rhodophyceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Rhodophyceae"),]
Rhodophyceae_tb_occur <- Rhodophyceae_tb[,1:91]
length(Rhodophyceae_tb_occur[,colSums(Rhodophyceae_tb_occur) > 0])## [1] 0Rappemonads_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Rappemonads"),]
Rappemonads_tb_occur <- Rappemonads_tb[,1:91]
length(Rappemonads_tb_occur[,colSums(Rappemonads_tb_occur) > 0])## [1] 0MOCH_1_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "MOCH-1"),]
MOCH_1_tb_occur <- MOCH_1_tb[,1:91]
length(MOCH_1_tb_occur[,colSums(MOCH_1_tb_occur) > 0])## [1] 0MOCH_2_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "MOCH-2"),]
MOCH_2_tb_occur <- MOCH_2_tb[,1:91]
length(MOCH_2_tb_occur[,colSums(MOCH_2_tb_occur) > 0])## [1] 0MOCH_5_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "MOCH-5"),]
MOCH_5_tb_occur <- MOCH_5_tb[,1:91]
length(MOCH_5_tb_occur[,colSums(MOCH_5_tb_occur) > 0])## [1] 0Prasinophyceae_clade_VII_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Prasinophyceae_clade-VII"),]
Prasinophyceae_clade_VII_tb_occur <- Prasinophyceae_clade_VII_tb[,1:91]
length(Prasinophyceae_clade_VII_tb_occur[,colSums(Prasinophyceae_clade_VII_tb_occur) > 0])## [1] 0Prasinophyceae_clade_IX_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Prasinophyceae_clade-IX"),]
Prasinophyceae_clade_IX_tb_occur <- Prasinophyceae_clade_IX_tb[,1:91]
length(Prasinophyceae_clade_IX_tb_occur[,colSums(Prasinophyceae_clade_IX_tb_occur) > 0])## [1] 0Pyramimonadaceae_tb <- tb18_phototrophs[which(tb18_phototrophs$classif == "Pyramimonadaceae"),]
Pyramimonadaceae_tb_occur <- Pyramimonadaceae_tb[,1:91]
length(Pyramimonadaceae_tb_occur[,colSums(Pyramimonadaceae_tb_occur) > 0])## [1] 0## reads_per_class OTUs_per_class
## Bacillariophyceae 3636 98
## Bolidophyceae 2971 15
## Chlorarachniophyceae 3335 70
## Chrysophyceae 79873 361
## Cryptophyceae 9910 77## reads_per_class OTUs_per_class samples_per_class
## Dinophyceae 650673 9894 0
## Chrysophyceae 79873 361 0
## Prasinophyceae 51033 191 0
## Pelagophyceae 46796 339 0
## Dictyochophyceae 39444 237 0
## Prasinophyceae_clade-VII 23960 125 0
## MOCH-2 17109 131 0
## Prasinophyceae_clade-IX 11979 79 0
## Cryptophyceae 9910 77 0
## MOCH-1 4357 70 0
## Bacillariophyceae 3636 98 0
## Chlorarachniophyceae 3335 70 0
## Bolidophyceae 2971 15 0
## MOCH-5 2431 19 0
## Pinguiophyceae 1544 19 0
## Prymnesiophyceae 399 62 0
## Mamiellophyceae 340 32 0
## other_Prasinophyceae 332 8 0
## Eustigmatales 232 9 0
## Raphydophyceae 211 4 0
## Pyramimonadaceae 113 3 0
## Trebouxiophyceae 103 3 0
## Ulvophyceae 16 3 01.6.1.2) Relative values
## reads_per_class OTUs_per_class samples_per_class
## 100 100 0## reads_per_class OTUs_per_class samples_per_class
## Dinophyceae 68.434481808 83.50071736 0
## Chrysophyceae 8.400636519 3.04667061 0
## Prasinophyceae 5.367391778 1.61195038 0
## Pelagophyceae 4.921765635 2.86100093 0
## Dictyochophyceae 4.148519610 2.00016879 0
## Prasinophyceae_clade-VII 2.519991123 1.05494135 0
## MOCH-2 1.799437735 1.10557853 0
## Prasinophyceae_clade-IX 1.259890387 0.66672293 0
## Cryptophyceae 1.042283474 0.64984387 0
## MOCH-1 0.458247134 0.59076715 0
## Bacillariophyceae 0.382416015 0.82707401 0
## Chlorarachniophyceae 0.350758364 0.59076715 0
## Bolidophyceae 0.312474692 0.12659296 0
## MOCH-5 0.255680235 0.16035108 0
## Pinguiophyceae 0.162390079 0.16035108 0
## Prymnesiophyceae 0.041964794 0.52325091 0
## Mamiellophyceae 0.035759473 0.27006498 0
## other_Prasinophyceae 0.034918074 0.06751625 0
## Eustigmatales 0.024400582 0.07595578 0
## Raphydophyceae 0.022191908 0.03375812 0
## Pyramimonadaceae 0.011884766 0.02531859 0
## Trebouxiophyceae 0.010833017 0.02531859 0
## Ulvophyceae 0.001682799 0.02531859 0
Reads per class vs. OTUs per class:
Reads per class vs. samples in which they occurr:
1.6.2) Non-normalized data
## [1] 43734 99## Row.names st055_MD1013 st057_MD1042 st058_MD1080 st059_MD1100
## 1 OTU_1 579 5968 2609 1500
## 2 OTU_10 26 5 1 26
## 3 OTU_100 31 159 21 8
## 4 OTU_1000 0 95 26 21
## 5 OTU_10000 0 0 0 0## [1] 43734 98## st055_MD1013 st057_MD1042 st058_MD1080 st059_MD1100 st009_MD111
## OTU_1 579 5968 2609 1500 815
## OTU_10 26 5 1 26 309
## OTU_100 31 159 21 8 1340
## OTU_1000 0 95 26 21 0
## OTU_10000 0 0 0 0 0## [1] 43734 99## st055_MD1013 st057_MD1042 st058_MD1080 st059_MD1100 st009_MD111
## OTU_1 579 5968 2609 1500 815
## OTU_2 9289 16285 5140 1187 8207
## OTU_3 15 96 18 6 1061
## OTU_4 230 776 150 561 337
## OTU_5 68 513 287 604 396## [1] 13554 99## st055_MD1013 st057_MD1042 st058_MD1080 st059_MD1100 st009_MD111
## OTU_1 579 5968 2609 1500 815
## OTU_4 230 776 150 561 337
## OTU_18 1042 4241 5755 3019 1129
## OTU_25 1353 6434 4523 4370 3060
## OTU_33 185 745 1559 258 615## st055_MD1013 st057_MD1042 st058_MD1080 st059_MD1100 st009_MD111
## OTU_1 579 5968 2609 1500 815
## OTU_4 230 776 150 561 337
## OTU_18 1042 4241 5755 3019 1129
## OTU_25 1353 6434 4523 4370 3060
## OTU_33 185 745 1559 258 615## [1] 11319 91## [1] 91## [1] 91## [1] 91## [1] 91## [1] 90## [1] 91## [1] 0## [1] 0## [1] 0## [1] 89## [1] 0## [1] 80## [1] 48## [1] 31## [1] 0## [1] 5## [1] 62## [1] 4## Group.1 x
## 7 Dinophyceae 1769257
## 4 Chrysophyceae 192835
## 13 Pelagophyceae 121087
## 15 Prasinophyceae 111285
## 6 Dictyochophyceae 104205
## 17 Prasinophyceae_clade-VII 56610
## 10 MOCH-2 45703
## 16 Prasinophyceae_clade-IX 29715
## 5 Cryptophyceae 27260
## 9 MOCH-1 13716
## 3 Chlorarachniophyceae 10036
## 1 Bacillariophyceae 9195
## 2 Bolidophyceae 7156
## 11 MOCH-5 7015
## 14 Pinguiophyceae 5296
## 18 Prymnesiophyceae 1072
## 12 Mamiellophyceae 931
## 23 other_Prasinophyceae 850
## 20 Raphydophyceae 664
## 8 Eustigmatales 573
## 19 Pyramimonadaceae 254
## 21 Trebouxiophyceae 193
## 22 Ulvophyceae 50## Group.1 x
## 7 Dinophyceae 11319
## 4 Chrysophyceae 418
## 13 Pelagophyceae 386
## 6 Dictyochophyceae 264
## 15 Prasinophyceae 218
## 10 MOCH-2 153
## 17 Prasinophyceae_clade-VII 133
## 1 Bacillariophyceae 109
## 5 Cryptophyceae 95
## 16 Prasinophyceae_clade-IX 86
## 9 MOCH-1 83
## 3 Chlorarachniophyceae 80
## 18 Prymnesiophyceae 74
## 12 Mamiellophyceae 35
## 14 Pinguiophyceae 27
## 11 MOCH-5 25
## 2 Bolidophyceae 16
## 23 other_Prasinophyceae 11
## 8 Eustigmatales 9
## 20 Raphydophyceae 4
## 19 Pyramimonadaceae 3
## 21 Trebouxiophyceae 3
## 22 Ulvophyceae 3## reads_per_class OTUs_per_class
## Bacillariophyceae 9195 109
## Bolidophyceae 7156 16
## Chlorarachniophyceae 10036 80
## Chrysophyceae 192835 418
## Cryptophyceae 27260 95## reads_per_class OTUs_per_class samples_per_class
## Dinophyceae 1769257 11319 92
## Chrysophyceae 192835 418 92
## Pelagophyceae 121087 386 92
## Prasinophyceae 111285 218 113
## Dictyochophyceae 104205 264 116
## Prasinophyceae_clade-VII 56610 133 103
## MOCH-2 45703 153 112
## Prasinophyceae_clade-IX 29715 86 112
## Cryptophyceae 27260 95 108
## MOCH-1 13716 83 111
## Chlorarachniophyceae 10036 80 97
## Bacillariophyceae 9195 109 65
## Bolidophyceae 7156 16 35
## MOCH-5 7015 25 75
## Pinguiophyceae 5296 27 75
## Prymnesiophyceae 1072 74 50
## Mamiellophyceae 931 35 18
## other_Prasinophyceae 850 11 1
## Raphydophyceae 664 4 1
## Eustigmatales 573 9 1
## Pyramimonadaceae 254 3 1
## Trebouxiophyceae 193 3 1
## Ulvophyceae 50 3 1## reads_per_class OTUs_per_class samples_per_class
## 100.000 100.000 1617.582## reads_per_class OTUs_per_class samples_per_class
## Dinophyceae 70.349365675 83.51040283 101.098901
## Chrysophyceae 7.667523672 3.08396045 101.098901
## Pelagophyceae 4.814672849 2.84786779 101.098901
## Prasinophyceae 4.424924790 1.60838129 124.175824
## Dictyochophyceae 4.143409154 1.94776450 127.472527
## Prasinophyceae_clade-VII 2.250932222 0.98126014 113.186813
## MOCH-2 1.817247047 1.12881806 123.076923
## Prasinophyceae_clade-IX 1.181530666 0.63449904 123.076923
## Cryptophyceae 1.083914721 0.70090010 118.681319
## MOCH-1 0.545376901 0.61236535 121.978022
## Chlorarachniophyceae 0.399052390 0.59023167 106.593407
## Bacillariophyceae 0.365612467 0.80419064 71.428571
## Bolidophyceae 0.284537555 0.11804633 38.461538
## MOCH-5 0.278931099 0.18444740 82.417582
## Pinguiophyceae 0.210580057 0.19920319 82.417582
## Prymnesiophyceae 0.042624966 0.54596429 54.945055
## Mamiellophyceae 0.037018511 0.25822635 19.780220
## other_Prasinophyceae 0.033797781 0.08115685 1.098901
## Raphydophyceae 0.026402031 0.02951158 1.098901
## Eustigmatales 0.022783681 0.06640106 1.098901
## Pyramimonadaceae 0.010099572 0.02213369 1.098901
## Trebouxiophyceae 0.007674084 0.02213369 1.098901
## Ulvophyceae 0.001988105 0.02213369 1.098901Reads per class vs. OTUs per class:
Reads OTUs per class vs. samples in which they occurr:
